A Recovery Method for Abnormal Radar Parameters Based on Improved VAE Model

To address the problem of abnormal radar parameters caused by electromagnetic interferences, a recovery method for abnormal radar parameters based on improved Variational Autoencoder model with self-attention (SA-VAE) is proposed. By incorporating a self-attention mechanism into the encoder of the VAE, the model can capture the complex internal dependencies of radar parameters and enhance the feature extraction capabilities of the model. Simulation results indicate that the recovery deviation of abnormal radar parameters using the proposed method is consistently within 5%, which demonstrates that the SA-VAE model has higher reconstruction accuracy compared to the original VAE model.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1109/apcap62011.2024.10881456
Citations
1
Primary Topic
Geophysical Methods and Applications
Type
article
Field-Weighted Citation Impact
0.34
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A Recovery Method for Abnormal Radar Parameters Based on Improved VAE Model

Tianran Zhang, Fang Ye, Yisong Liu, Jianfei Qian
1 citations
Geophysical Methods and Applications
0.34
article

A Recovery Method for Abnormal Radar Parameters Based on Improved VAE Model

Tianran Zhang, Fang Ye, Yisong Liu, Jianfei Qian
article en
1 citations

Abstract

To address the problem of abnormal radar parameters caused by electromagnetic interferences, a recovery method for abnormal radar parameters based on improved Variational Autoencoder model with self-attention (SA-VAE) is proposed. By incorporating a self-attention mechanism into the encoder of the VAE, the model can capture the complex internal dependencies of radar parameters and enhance the feature extraction capabilities of the model. Simulation results indicate that the recovery deviation of abnormal radar parameters using the proposed method is consistently within 5%, which demonstrates that the SA-VAE model has higher reconstruction accuracy compared to the original VAE model.

Harbin Engineering University (CN), Beijing Electronic Science and Technology Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 36%
Geophysical Methods and Applications
0.34
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